Title: Semantic measures as information quality criteria for query routing processes

Authors: Crishane Freire; Bruno F.F. Souza; Ana Carolina Salgado; Damires Souza; Maria C.M. Batista

Addresses: Center for Informatics, Federal University of Pernambuco, Av. Jornalista Anibal Fernandes, s/n, 50.740-560, Recife, Pernambuco, Brazil ' Center for Informatics, Federal University of Pernambuco, Av. Jornalista Anibal Fernandes, s/n, 50.740-560, Recife, Pernambuco, Brazil ' Center for Informatics, Federal University of Pernambuco, Av. Jornalista Anibal Fernandes, s/n, 50.740-560, Recife, Pernambuco, Brazil ' Federal Institute of Education, Science and Technology of Paraiba, Av. Primeiro de Maio, 720, Jaguaribe, 58.015-430, João Pessoa, Paraíba, Brazil ' Federal Rural University of Pernambuco, Rua Dom Manoel de Medeiros, s/n, Dois Irmãos, 52.171-900, Recife, Pernambuco, Brazil

Abstract: Query answering has been addressed as a key issue in distributed environments such as peer data management systems (PDMS). An important step in this process regards query routing, i.e., how to find peers (data sources) that are most likely to provide results according to the submitted query. In this process, queries are reformulated and propagated through network peers using the semantic mappings between neighbour peers' schemas. The successive processes of query reformulation may result in a semantic loss of the original query, i.e., concepts which belong to the original query may be lost when reformulated queries are produced. Thereby, this work proposes the use of semantic measures obtained from information quality (IQ) criteria aiming to avoid or minimise this semantic loss. Moreover, it combines semantic information and IQ, by presenting a model, which is instantiated to illustrate how this proposal produces the semantic measures and enhances query routing processes.

Keywords: peer data management systems; PDMS; query routing; information quality; query reformulation; semantics; semantic mappings; semantic measures; information retrieval.

DOI: 10.1504/IJBIDM.2013.057745

International Journal of Business Intelligence and Data Mining, 2013 Vol.8 No.2, pp.167 - 183

Published online: 28 Jun 2014 *

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